Reconfigurable intelligent surface(RIS)is more likely to develop into extremely large-scale RIS(XL-RIS)to efficiently boost the system capacity for future 6G communications.Beam training is an effec-tive way to acquire channel state information(CSI)for XL-RIS.Existing beam training schemes rely on the far-field codebook.However,due to the large aper-ture of XL-RIS,the scatters are more likely to be in the near-field region of XL-RIS.The far-field code-book mismatches the near-field channel model.Thus,the existing far-field beam training scheme will cause severe performance loss in the XL-RIS assisted near-field communications.To solve this problem,we pro-pose the efficient near-field beam training schemes by designing the near-field codebook to match the near-field channel model.Specifically,we firstly design the near-field codebook by considering the near-field cascaded array steering vector of XL-RIS.Then,the optimal codeword for XL-RIS is obtained by the ex-hausted training procedure.To reduce the beam train-ing overhead,we further design a hierarchical near-field codebook and propose the corresponding hierar-chical near-field beam training scheme,where differ-ent levels of sub-codebooks are searched in turn with reduced codebook size.Simulation results show the proposed near-field beam training schemes outperform the existing far-field beam training scheme.

Xiuhong Wei;Linglong Dai;Yajun Zhao;Guanghui Yu;Xiangyang Duan

Beijing National Research Center for Information Science and Technology(BNRist)as well as the Department of Electronic Engineering,Tsinghua University,Beijing 100084,China;ZTE Corporation,Shenzhen 518038,China

中国通信（英文版）

[1]Xiuhong Wei;Linglong Dai;Yajun Zhao;Guanghui Yu;Xiangyang Duan-.Codebook Design and Beam Training for Extremely Large-Scale RIS:Far-Field or Near-Field?)[J].中国通信（英文版）,2022(06):193-204

Codebook,codebook,codeword,hausted,codebooks

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